In systems for identifying road lanes, image processing is based on edge detection. Classic versions select the edges which are to be used for road lane prediction by analysing the convolution responses. The N edges having the highest convolution responses are used, and their permutations are examined. The aforesaid approach enables proper functioning of the system in many cases since the contrast difference is usually highest between the road surface and the road surface marking.
In certain circumstances, however, structures can occur whose contrast difference, i.e. black difference, is high, but which are no road lane. These include, for example, headlights or reflectors which are reflected by the road in tunnels, thus causing road lanes to be estimated incorrectly.